Learning objectives
(HL) Outline NoSQL document and key-value stores, cloud databases, spatial databases and in-memory databases, and match each to uses such as e-commerce, geographic information systems, social media and software-as-a-service
(HL) Explain the purpose of a data warehouse and its properties: subject-oriented, integrated, time-variant, non-volatile, append-only and optimised for analytical queries
(HL) Explain how online analytical processing and data-mining techniques (classification, clustering, regression, association rules, sequential patterns and anomaly detection) turn stored data into business intelligence
(HL) Describe how a distributed database partitions and replicates data across sites while maintaining consistency, ACID transactions, concurrency control, security, fault tolerance, location transparency, global query processing and scalability
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